nep-fmk New Economics Papers
on Financial Markets
Issue of 2018‒03‒05
six papers chosen by

  1. Stock returns forecast: an examination by means of Artificial Neural Networks By Martin Iglesias Caride; Aurelio F. Bariviera; Laura Lanzarini
  2. The Fama 3 and Fama 5 factor models under a machine learning framework By Periklis Gogas; Theofilos Papadimitriou; Dimitrios Karagkiozis
  3. Immediate Causality Network of Stock Markets By Li Zhou; Lu Qiu; Changgui Gu; Huijie Yang
  4. Short-Selling Bans and the Global Financial Crisis: Are they Inter-Connected? By Martin T. Bohl, Badye Essid, Pierre Siklos
  5. Speculative Activity and Returns to Volatility of Chinese Major Agricultural Commodity Futures By Martin T. Bohl, Pierre Siklos, Claudia Wellenreuther
  6. Quantifying the Impact of the November 2014 Shanghai-Hong Kong Stock Connect By Richard C. K. Burdekin, Pierre Siklos

  1. By: Martin Iglesias Caride; Aurelio F. Bariviera; Laura Lanzarini
    Abstract: The validity of the Efficient Market Hypothesis has been under severe scrutiny since several decades. However, the evidence against it is not conclusive. Artificial Neural Networks provide a model-free means to analize the prediction power of past returns on current returns. This chapter analizes the predictability in the intraday Brazilian stock market using a backpropagation Artificial Neural Network. We selected 20 stocks from Bovespa index, according to different market capitalization, as a proxy for stock size. We find that predictability is related to capitalization. In particular, larger stocks are less predictable than smaller ones.
    Date: 2018–01
  2. By: Periklis Gogas (Department of Economics, Democritus University of Thrace, Greece; Rimini Centre for Economic Analysis); Theofilos Papadimitriou (Department of Economics, Democritus University of Thrace, Greece); Dimitrios Karagkiozis (Department of Economics, Democritus University of Thrace, Greece)
    Abstract: We examine four empirical models which are popular in money and stock markets world. These models are Fama – French 3 & 5 factors model, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT) model. These tools are intensively used by investors and market professionals as an important part of the investment decision process and for the evaluation of the applied investment strategies. The last years, several surveys and studies have done, and various methodologies were implemented to evaluate the effectiveness of these four models. The methodological approach of the current thesis focuses on the Support Vector Regression (SVR). This method is running in comparison with the Ordinary Least Squares linear regression.
    Keywords: stock markets, stock returns, machine learning, support vector regression
    JEL: F31 F37 C45 C5
    Date: 2018–02
  3. By: Li Zhou; Lu Qiu; Changgui Gu; Huijie Yang
    Abstract: A financial system contains many elements networked by their relationships. Extensive works show that topological structure of the network stores rich information on evolutionary behaviors of the system such as early warning signals of collapses and/or crises. Existing works focus mainly on the network structure within a single stock market, while a collapse/crisis occurs in a macro-scale covering several or even all markets in the world. This mismatch of scale leads to unacceptable noise to the topological structure, and lack of information stored in relationships between different markets. In this work by using the transfer entropy we reconstruct the influential network between ten typical stock markets distributed in the world. Interesting findings include, before a financial crisis the connection strength reaches a maxima, which can act as an early warning signal of financial crises; The markets in America are mono-directionally and strongly influenced by that in Europe and act as the center; Some strongly linked pairs have also close correlations. The findings are helpful in understanding the evolution and modelling the dynamical process of the global financial system.
    Date: 2018–02
  4. By: Martin T. Bohl, Badye Essid, Pierre Siklos (Wilfrid Laurier University)
    Abstract: This paper begins with the observation that short-selling bans spread globally in 2008. We find some evidence that the bans were unsuccessful at least insofar as they did not take into account the global component a short-selling ban which reduced equity returns in about a third of the 17 countries sampled, most notably in some of the major advanced economies. In the individual countries we examine, the bans had relatively little impact. Our results are suggestive as evidence that the bans stemmed further deterioration in stock prices that policy makers sought to avoid, at least in a few economies.
    Keywords: Short-selling bans, Spillovers, Stock markets, Dynamic conditional correlations
    JEL: G10 G12
    Date: 2018–01–30
  5. By: Martin T. Bohl, Pierre Siklos, Claudia Wellenreuther (Wilfrid Laurier University)
    Abstract: Chinese futures markets for agricultural commodities are among the fastest growing futures markets in the world and trading behaviour in those markets is perceived as highly speculative. Therefore, we empirically investigate whether speculative activity in Chinese futures markets for agricultural commodities destabilizes futures returns. To capture speculative activity a speculation and a hedging ratio are used. Applying GARCH models we first analyse the influence of both ratios on the conditional volatility of eight heavily traded Chinese futures contracts. Additionally, VAR models in conjunction with Granger causality tests, impulse-response analyses and variance decompositions are used to obtain insight into the lead-lag relationship between speculative activity and returns volatility. For most of the commodities, we find a positive influence of the speculation ratio on conditional volatility. The results relying on the hedging ratio are inconclusive.
    Keywords: Speculation Ratio, Returns Volatility, Chinese Futures Markets, Agricultural Commodities
    JEL: E44 F30 G12 G13 G15
    Date: 2018–01–30
  6. By: Richard C. K. Burdekin, Pierre Siklos (Wilfrid Laurier University)
    Abstract: The November 2014 Shanghai-Hong Kong Stock Connect represented an important step in China’s capital account liberalization, allowing relatively free movement of investor funds between the two markets for the first time. We offer a quantification of the effects of the new program, examining Northbound and Southbound flows of funds over the first two years of the Stock Connect. While controlling for other sentiment and liquidity effects, we test how these flows may have affected the extent of the premium seen for local A-share listings in Shanghai relative to the prices accruing to the same companies in Hong Kong market trading.
    Keywords: Capital account liberalization; Stock returns; Sentiment; Shanghai; Hong Kong
    JEL: G15
    Date: 2018–01–30

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